Have you signed in to OSF lately? Towson University is now an OSF Member, which means you can log in to OSF with your Towson login and password.
Conducting your research through the Towson OSF platform is a strategic way to enhance transparency, foster collaboration, and increase the visibility of your research. It allows you to affiliate your public research with Towson University on OSF and discover other affiliated research. If your research is not yet public, now might be a good time to consider sharing your existing or future work.
To start affiliating your research, visit osf.io and choose “sign in with my institution.”
Then select Towson University from the drop-down on the next screen. You will be directed to login with your Towson login and password. Once you set up the connection by logging in this way one time, you can continue to login with your existing OSF username and password or use the new institutional login.
For more information, you can view help guides on signing in with your institution and affiliating your projects. You’ll be able to view the Towson University affiliated research through our new landing page.
All of the videos of the NVIVO workshops are posted here.
Changes to ArcGIS Licensing in 2024
Published by Rosenblum, Andrew B. on August 12, 2024 12:00 am in General
For more information about the GIS resources that are available to the TU community, check out our page, Towson University GIS Tools.
Yesterday, DMPTool.org released the Winter 2023 Newsletter in which the latest updates of the support for the new NIH DMSP requirements are announced.
***Today, we removed the older NIH DMSP templates, and all newly created plans will now be directed to the new NIH template. Previously created plans are still accessible; this only affects new plans.***
The DMPTool NIH Template Working Group is focused on supporting the upcoming NIH requirements for data sharing. This hard-working group, chaired by Nina Exner of Virginia Commonwealth University, has developed several new resources for the community."
Learn more here.
On October 29, 2020, NIH, the National Institutes of Health (NIH) is issuing this final NIH Policy for Data Management and Sharing (DMS Policy) to promote the management and sharing of scientific data generated from NIH-funded or conducted research. This Policy establishes the requirements of submission of Data Management and Sharing Plans (hereinafter Plans) and compliance with NIH Institute, Center, or Office (ICO)-approved Plans. It also emphasizes the importance of good data management practices and establishes the expectation for maximizing the appropriate sharing of scientific data generated from NIH-funded or conducted research, with justified limitations or exceptions. This Policy applies to research funded or conducted by NIH that results in the generation of scientific data.
The official notice can be find here. The new policy will be effective on January 25, 2023.
Welcome to the Research Guide of Data!
We are working on providing the Research Data Services covering every phase of the Data Lifecycle, from Plan, Collect, Assure, Describe, Preserve, Discover to Integrate and Analyze,(DataOne.org) both for the research projects and the courses.
The phases of Data Lifecycle can be found in the section of Research Data Services, in which some resources of Data Analysis/Visualization and Data Repositiory/Sharing are also provided. The resources of datasets are still in the section of Data Repository/Sharing.
If you are looking for some resources about Data Analysis/Visualization, you may want to take a look at here.
To learn more about the research data services provided by the Cook Library, please contact Songyao Chen (schen@towson.edu), the Data Science Librarian.
Please refer to below for some of the quick links to the section you need: (you can also find all the section in the left bar)
Data Management Plan: DMPTool.org, Funder Requirements, etc.
Data Repository/Datasets: ScholarWorks, Datasets of different disciplines, Dataverse, ICPSR, re3data.org, OSF, Kaggle, ORCID, etc.
Data Visualization/Analysis: Data Analysis phases, Data Visualization/Analysis Tools, Mapping tools, etc.
Research Data Management (RDM) is a broad concept that includes processes undertaken to create organized, documented, accessible, and reusable quality research data. The role of the librarian is to support researchers through the research data lifecycle.
The processes involved in RDM are more complex than simply backing up data on a thumb drive and ensuring that sensitive data is kept secure. Managing data includes using file naming conventions, organizing files, creating metadata, controlling access to data, backing up data, citing data, and more. There are checklists online which point to the considerations and processes in RDM .
Citation:
"Keeping Up With… Research Data Management", American Library Association, April 17, 2018.
http://www.ala.org/acrl/publications/keeping_up_with/rdm (Accessed August 12, 2022)
Document ID: 0c271f0c-e0ba-4306-8278-cdcff353a83c
Why Data Management is important and what could happened when there is no data management has ever been applied in your research project? The video below will tell you!
It's important to cite data right. Proper citation ensures that research data can be:
Citing data is straightforward. Each citation must include the basic elements that allow a unique dataset to be identified over time:
